lets_plot.geom_line

lets_plot.geom_line(mapping=None, *, data=None, stat=None, position=None, show_legend=None, sampling=None, tooltips=None, **other_args)

Connect points in the order of the variable on the x axis. In case points need to be connected in the order in which they appear in the data, use geom_path().

Parameters

• mapping (FeatureSpec) – Set of aesthetic mappings created by aes() function. Aesthetic mappings describe the way that variables in the data are mapped to plot “aesthetics”.

• data (dict or DataFrame) – The data to be displayed in this layer. If None, the default, the data is inherited from the plot data as specified in the call to ggplot.

• stat (str, default=’identity’) – The statistical transformation to use on the data for this layer, as a string. Supported transformations: ‘identity’ (leaves the data unchanged), ‘count’ (counts number of points with same x-axis coordinate), ‘bin’ (counts number of points with x-axis coordinate in the same bin), ‘smooth’ (performs smoothing - linear default), ‘density’ (computes and draws kernel density estimate).

• position (str or FeatureSpec) – Position adjustment, either as a string (‘identity’, ‘stack’, ‘dodge’, …), or the result of a call to a position adjustment function.

• show_legend (bool, default=True) – False - do not show legend for this layer.

• sampling (FeatureSpec) – Result of the call to the sampling_xxx() function. Value None (or ‘none’) will disable sampling for this layer.

• tooltips (layer_tooltips) – Result of the call to the layer_tooltips() function. Specifies appearance, style and content.

• other_args – Other arguments passed on to the layer. These are often aesthetics settings used to set an aesthetic to a fixed value, like color=’red’, fill=’blue’, size=3 or shape=21. They may also be parameters to the paired geom/stat.

Returns

Geom object specification.

Return type

LayerSpec

Note

geom_line() connects the observations in the order of the variable on the x axis. geom_line() can be used to plot time series.

geom_line() understands the following aesthetics mappings:

• x : x-axis value.

• y : y-axis value.

• alpha : transparency level of a layer. Understands numbers between 0 and 1.

• color (colour) : color of a geometry. Can be continuous or discrete. For continuous value this will be a color gradient between two colors.

• linetype : type of the line. Codes and names: 0 = ‘blank’, 1 = ‘solid’, 2 = ‘dashed’, 3 = ‘dotted’, 4 = ‘dotdash’, 5 = ‘longdash’, 6 = ‘twodash.

• size : line width.

Examples

>>> import numpy as np
>>> from lets_plot import *
>>> LetsPlot.setup_html()
>>> x = np.linspace(-4 * np.pi, 4 * np.pi, 100)
>>> y = np.sin(x)
>>> ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + geom_line()

>>> import numpy as np
>>> import pandas as pd
>>> from lets_plot import *
>>> LetsPlot.setup_html()
>>> np.random.seed(42)
>>> t = np.arange(100)
>>> x1 = np.cumsum(np.random.normal(size=t.size))
>>> x2 = np.cumsum(np.random.normal(size=t.size))
>>> df = pd.DataFrame({'t': t, 'x1': x1, 'x2': x2})
>>> df = pd.melt(df, id_vars=['t'], value_vars=['x1', 'x2'])
>>> ggplot(df, aes(x='t', y='value', group='variable')) + \
>>>     geom_line(aes(color='variable'), size=1, alpha=0.5) + \
>>>     geom_line(stat='smooth', color='red', linetype='longdash')